# Development of a Mobile Cognitive App for Detecting and Monitoring Change in Preclinical Alzheimer's Disease

> **NIH NIH K23** · UNIVERSITY OF PENNSYLVANIA · 2020 · $171,315

## Abstract

PROJECT SUMMARY/ABSTRACT
The diagnosis and monitoring of cognitive symptoms in Alzheimer's disease and related dementias (ADRD)
requires valid and reliable assessment of cognitive change. Current limitations in traditionally used testing
measures include the length of testing, low engagement, day-to day variability, few data points, and limits in
the ability to identify subtle differences in normal individuals at risk for cognitive decline. Many of the currently
available computerized assessment tools either (1) have not been updated to incorporate current cognitive
neuroscience theory (2) do not target measures associated with the earliest neuroanatomical changes in brain
aging and neurodegeneration and/or (3) do not capitalize on the benefits of digital technology to maximize valid
and reliable cognitive data collection. Mobile and sensitive measures for detection of subtle cognitive change in
preclinical Alzheimer's Disease (AD) along with biomarker measures of molecular pathology and
neurodegeneration will combine to identify individuals who will benefit most from interventions. This project will
include development and validation of two, engaging, user-friendly and empirically based cognitive assessment
tasks and create the Mobile Cognitive App Performance Platform (mCAPP). The two cognitive tests will
comprise: (1) a memory card game (already designed and pilot-tested) that includes similar pairs of objects
and increasing memory load and (2) an executive functioning and processing speed test using a code
completion game. The cognitive tests will include a high-ceiling and low floor to capture a range of ability, burst
testing to increase reliability of the data, gamified design to increase engagement and motivation, and mobile-
based design for capturing data in all environments. The mCAPP will be validated in a well-characterized
cohort of older adults with normal cognition in the Penn Alzheimer's Disease Center. The cohort will
concurrently complete a neuropsychological battery, high resolution structural MRI and amyloid PET imaging
through funded P32 and R01 projects, which will be leveraged in this study to understand the relationships
between cognitive performance and neuroimaging biomarker status. Structural imaging targets will include
areas of the medial temporal lobe implicated in the earliest stages of preclinical Alzheimer's disease. The
purpose of the mCAPP is to collect reliable and valid cognitive data to detect very early signs of AD-related
cognitive change and remotely track response to interventions. Remotely administered, engaging cognitive
tests that are sensitive to the earliest changes in individuals at risk for AD have the potential to expand our
knowledge of cognition in aging, lead to early detection of cognitive variability, monitor change over time and
change as a result of intervention. This project will facilitate collection of data to support larger studies with the
mCAPP and career development opportunities in...

## Key facts

- **NIH application ID:** 10054911
- **Project number:** 1K23AG065499-01A1
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** DAWN J MECHANIC-HAMILTON
- **Activity code:** K23 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $171,315
- **Award type:** 1
- **Project period:** 2020-09-15 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10054911

## Citation

> US National Institutes of Health, RePORTER application 10054911, Development of a Mobile Cognitive App for Detecting and Monitoring Change in Preclinical Alzheimer's Disease (1K23AG065499-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10054911. Licensed CC0.

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